Turning AI insights into meaningful actions: The future of healthcare navigation

We’ve been talking about artificial intelligence in healthcare for years. It’s no longer “the wave of the future” – it’s here, and it’s accelerating, and those who are still stuck in proof-of-concept mode may already be lagging behind. For benefits leaders, the pace of this change can be dizzying. In the blink of an eye, artificial intelligence has gone from curiosity to cornerstone.

For example: recently Medical City Index Survey A study co-sponsored by Quantum Health found that 72% of advisors now advise clients on artificial intelligence in benefit plans—nearly one-third do so regularly, up from just 20% a year ago. But adoption is uneven, results are inconsistent, and too many employers are stuck with tools that add noise rather than drive results. In addition to keeping up with the rapid advances in AI, HR leaders will need to help cut through the hype to determine where AI-driven navigation can really make a difference—engaging members and providers, driving timely action, and delivering measurable value.

Here are some areas where I believe there is the greatest need and the greatest hope of making a meaningful impact.

From automation to anticipation
In healthcare navigation, the true power of AI is not just in answering questions or automating workflows, but in anticipating needs and taking action in real time. With the right data, predictive analytics can flag when someone faces a gap in care, avoidable costs, or a high-risk health event. The value lies in timely intervention to prevent problems before they escalate.

This shift from automation to anticipation is redefining healthcare navigation. For example, half of the counselors surveyed in the Index reported persistent and costly gaps in navigation, particularly around personalization, care coordination and engagement. Artificial intelligence can bridge these gaps, enabling proactive, clinically embedded navigation to guide members seamlessly through their healthcare journey.

For example, consider people preparing for their first chemotherapy appointment. Using artificial intelligence, the system can flag missing authorizations up to three days before an appointment, allowing care coordinators to resolve issues before they delay treatment and significantly impact member care. This is more than just an administrative fix—it’s a time to build trust and reassurance for patients as they navigate one of the most challenging experiences of their lives.

Precise cost management through predictive analytics
Controlling health care costs remains one of the biggest challenges facing employers, with companies preparing for a median 9% rise in health care costs next year after two years of record increases, according to the Business Health Group (BGH) annual survey. To avoid passing these increases on to employees, HR leaders must root out inefficiencies and eliminate avoidable costs wherever possible. Artificial intelligence provides powerful solutions by identifying cost drivers and inefficiencies before they escalate.

AI-driven navigation uses real-time data to connect actions to downstream savings and quality outcomes. At Quantum Health, for example, predictive models can spot patterns that often result in unnecessary costs (such as delayed care or avoidable emergency room visits) and trigger real-time interventions.

Another area of ​​rapid growth is pharmacy spending, especially high-cost therapies such as GLP-1. According to the BGH report, GLP-1 is one of the fastest growing cost drivers next year. Artificial intelligence can guide real-time decision-making at scale, flagging where these treatments can add real clinical value and which alternatives might be more effective.

Strengthen engagement and close care gaps
Member engagement is always at the forefront of benefits leaders’ minds. But real engagement is no longer about increasing touch points; This is about creating targeted, high-value moments. AI can help identify members most at risk of being overlooked and suggest the right interventions – whether care coordination, welfare coaching or behavioral nudges – ensuring timely, relevant support.

But this is where striking the right balance between AI and human expertise can have a significant impact on outcomes. AI can and should flag issues and even suggest fixes, but it needs human support to provide reassurance, empathy, and trust—elements that truly personalize and transform the member experience. In this equation, technology creates space for more empathy, not less.

Differentiate through actions, not just insights
The benefits space is awash with AI tools—but the real difference lies in execution. Many navigation solutions provide insights but leave it up to members and employers to determine next steps. The most effective models go a step further, combining AI-driven intelligence with skilled care teams capable of acting on those insights in real time.

For example, while chatbots and virtual assistants can manage basic tasks, they perform poorly in complex or high-stakes situations. The real breakthroughs will come when AI doesn’t just give you information – it helps you take action. When AI-driven intelligence is combined with caring human experts who take immediate action to solve problems, members and providers get more than just answers, they get solutions.

The future of artificial intelligence in benefits administration
The next era of benefits administration will not be defined by who has AI, but who can translate AI insights into meaningful actions for members, providers and employers.

This is not about a choice between AI and humans. It's about intentionally bringing the two together to achieve the results we all care about. By combining real-time AI with human compassion, we can deliver smarter, more connected and truly human healthcare navigation.